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- SAP HANA Quick Guide - Learn SAP HANA starting from Overview, In Memory Computing Engine, Studio, Studio Administration View, System Monitor, Information Modeler.
- IDES is a demo SAP system developed by SAP AG used for learning and training and purpose. IDES stand for Internet Demonstration and Evaluation System.
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SAP HANA Quick Guide. SAP HANA - Quick Guide. SAP HANA - Overview. SAP HANA is a combination of HANA Database, Data Modeling, HANA Administration and Data Provisioning in one single suite. In SAP HANA, HANA stands for High- Performance Analytic Appliance. According to former SAP executive, Dr. Vishal Sikka, HANA stands for Hasso’s New Architecture.
HANA developed interest by mid- 2. Business Warehouse needs after that. Features of SAP HANAThe main features of SAP HANA are given below . A key to this is the effective and efficient use of data and information by analyst and managers. HANA overcomes the limitations mentioned below .
This onsite visit includes deployment of HANA system in Data Center, Connectivity to Organization Network, SAP system ID adaption, updates from Solution Manager, SAP Router Connectivity, SSL Enablement and other system configuration. Customer/Client starts with connectivity of Data Source system and BI clients.
HANA Studio Installation is completed on local system and HANA system is added to perform Data modeling and administration. SAP HANA - In- Memory Computing Engine. An In- Memory database means all the data from source system is stored in a RAM memory. In a conventional Database system, all data is stored in hard disk. SAP HANA In- Memory Database wastes no time in loading the data from hard disk to RAM. It provides faster access of data to multicore CPUs for information processing and analysis.
Features of In- Memory Database. The main features of SAP HANA in- memory database are . SAP HANA In- Memory database reads data in 5 nanoseconds. It means, memory reads in HANA database are 1 million times faster than a conventional database hard disk memory reads. Analysts want to see current data immediately in real time and do not want to wait for data until it is loaded to SAP BW system. SAP HANA In- Memory processing allows loading of real time data with use of various data provisioning techniques.
Advantages of In- Memory Database. HANA database takes advantage of in- memory processing to deliver the fastest data- retrieval speeds, which is enticing to companies struggling with high- scale online transactions or timely forecasting and planning.
Disk- based storage is still the enterprise standard and price of RAM has been declining steadily, so memory- intensive architectures will eventually replace slow, mechanical spinning disks and will lower the cost of data storage. In- Memory Column- based storage provides data compression up to 1. This speed advantages offered by RAM storage system are further enhanced by the use of multi- core CPUs, multiple CPUs per node and multiple nodes per server in a distributed environment. SAP HANA - Studio. SAP HANA studio is an Eclipse- based tool.
SAP HANA studio is both, the central development environment and the main administration tool for HANA system. Additional features are . At the time of Studio installation, specify the features you want to install as per the role. To work on most recent version of HANA studio, Software Life Cycle Manager can be used for client update. SAP HANA Studio Perspectives / Features. SAP HANA Studio provides perspectives to work on the following HANA features.
You can choose Perspective in HANA Studio from the following option . General troubleshooting tools like tracing, the catalog browser and SQL Console are also included. SAP HANA Studio Database Development.
It provides Toolset for content development. It addresses, in particular, the Data. Marts and ABAP on SAP HANA scenarios, which do not include SAP HANA native application development (XS). SAP HANA Studio Application Development. SAP HANA system contains a small Web server, which can be used to host small applications.
It provides Toolset for developing SAP HANA native applications like application code written in Java and HTML. By default, all features are installed.
SAP HANA - Studio Administration View. To Perform HANA Database Administration and monitoring features, SAP HANA Administration Console Perspective can be used. Administrator Editor can be accessed in several ways . Overview Tab tells General Information like, Operational Status, start time of first and last started service, version, build date and time, Platform, hardware manufacturer, etc. Adding a HANA System to Studio.
Single or multiple systems can be added to HANA studio for administration and information modeling purpose. To add new HANA system, host name, instance number and database user name and password is required. Port 3. 61. 5 should be open to connect to Database. Port 3. 10. 15 Instance No 1.
Port 3. 00. 15 Instance No 0. SSh port should also be opened. Adding a System to Hana Studio. To add a system to HANA studio, follow the given steps. Right Click in Navigator space and click on Add System.
Enter HANA system details, i. Host name & Instance number and click next. Enter Database user name and password to connect to SAP HANA database.
Click on Next and then Finish. Once you click on Finish, HANA system will be added to System View for administration and modeling purpose. Each HANA system has two main sub- nodes, Catalog and Content.
Catalog and Content. Catalog. It contains all available Schemas i.
These models are organized in Packages. The content node provides different views on same physical data. SAP HANA - System Monitor. System Monitor in HANA studio provides an overview of all your HANA system at a glance. From System Monitor, you can drill down into details of an individual system in Administration Editor.
It tells about Data Disk, Log disk, Trace Disk, Alerts on resource usage with priority. The following Information is available in System Monitor . It enables to create modeling views at the top of database tables and implement business logic to create a meaningful report for analysis. Features of Information Modeler. Provides multiple views of transactional data stored in physical tables of HANA database for analysis and business logic purpose.
Informational modeler only works for column based storage tables. Information Modeling Views are consumed by Java or HTML based applications or SAP tools like SAP Lumira or Analysis Office for reporting purpose.
Also possible to use third party tools like MS Excel to connect to HANA and create reports. SAP HANA Modeling Views exploit real power of SAP HANA. There are three types of Information Views, defined as . Storing data in Column tables is not a new thing. Earlier it was assumed that storing data in Columnar based structure takes more memory size and not performance Optimized. With evolution of SAP HANA, HANA used column based data storage in Information views and presented the real benefits of columnar tables over Row based tables. Column Store. In a Column store table, Data is stored vertically.
So, similar data types come together as shown in the example above. It provides faster memory read and write operations with help of In- Memory Computing Engine. In a conventional database, data is stored in Row based structure i. SAP HANA stores data in both row and Column based structure. This provides Performance optimization, flexibility and data compression in HANA database.
Storing Data in Columnar based table has following benefits . Column based tables always perform better when running aggregate functions like Sum, Count, Max, Min. Row based storage is preferred when output has to return complete row. The example given below makes it easy to understand. In the above example, while running an Aggregate function (Sum) in sales column with Where clause, it will only use Date and Sales column while running SQL query so if it is column based storage table then it will be performance optimized, faster as data is required only from two columns.
While running a simple Select query, full row has to be printed in output so it is advisable to store table as Row based in this scenario. Information Modeling Views. Attribute View. Attributes are non- measurable elements in a database table. They represent master data and similar to characteristics of BW.
Attribute Views are dimensions in a database or are used to join dimensions or other attribute views in modeling. Important features are . It has at least one fact table that has measures and primary keys of dimension tables and surrounded by dimension tables contain master data. Important features are . Calculation view is a combination of base column tables, Attribute views and Analytic views to provide business logic.
Important features are . SAP HANA system consists of multiple components that are responsible to emphasize computing power of HANA system.
Most important component of SAP HANA system is Index Server, which contains SQL/MDX processor to handle query statements for database. HANA system contains Name Server, Preprocessor Server, Statistics Server and XS engine, which is used to communicate and host small web applications and various other components. Index Server. Index Server is heart of SAP HANA database system. It contains actual data and engines for processing that data.
When SQL or MDX is fired for SAP HANA system, an Index Server takes care of all these requests and processes them. All HANA processing takes place in Index Server. Index Server contains Data engines to handle all SQL/MDX statements that come to HANA database system.
It also has Persistence Layer that is responsible for durability of HANA system and ensures HANA system is restored to most recent state when there is restart of system failure. Index Server also has Session and Transaction Manager, which manage transactions and keep track of all running and closed transactions. Index Server . It segments all query requests and direct them to correct engine for the performance Optimization. It also ensures that all SQL/MDX requests are authorized and also provide error handling for efficient processing of these statements. It contains several engines and processors for query execution .
MDX Engine is responsible to handle queries and manipulates multidimensional data stored in OLAP cubes.